Role and Expectations of Family Caregivers in Hospital at Home in the <scp>US</scp> and Canada
Bibliographic record
Abstract
David M. Levine: Serves as editor-in-chief of the Journal of Advanced Home Medicine. Royalties from Biofourmis. Fees from The MetroHealth System. Scientific advisor at Feminai. Linda V. DeCherrie: employee at Dispatch Health. Gabrielle Schiller: none. Annabel Steiner: none. Albert Siu: is a full-time employee of the Icahn School of Medicine, which in turn has an ownership interest in a joint venture with Contessa Health, a venture that manages acute care services provided to patients in their homes through prospective bundled payment arrangements. Dr. Albert Siu has no financial interest in this venture. Bruce Leff: reported receiving personal consulting fees: Chartis Healthcare, the Aligned Health Group, the Kenes Group, and the West Health Institute. Stock options: Member of clinical advisory boards to Honor Care, Dispatch Health, Pager Health. Honoraria: Board of directors of the American Board of Internal Medicine Foundation, Ascension Health quality committee. Dr. Bruce Leff serves as executive editor of the Journal of Advanced Home Medicine. The authors declare no conflicts of interest. Text S1: HaH caregiving survey. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".